A New Application of CurvaTool Semi-Automatic Approach to Qualitatively Detect Geological Lineaments

Research Article| August 01, 2017 A New Application of Curvatool Semi-automatic Approach To Qualitatively Detect Geological Lineaments Sabrina Bonetto; Sabrina Bonetto 1 Department of Earth Sciences, University of Turin, Valperga Caluso 35, 10125 Turin, Italy; sabrina.bonetto@unito.it 1Corresponding author: Sabrina Bonetto, email: sabrina.bonetto @unito.it Search for other works by this author on: GSW Google Scholar Anna Facello; Anna Facello CNR-IRPI, Strada delle Cacce, 73 - 10135 Turin, Italy; anna.facello@irpi.cnr.it Search for other works by this author on: GSW Google Scholar Gessica; Umili Gessica; Umili Department of Earth Sciences, University of Turin, Valperga Caluso 35, 10125 Turin, Italy; gessica.umili@unito.it Search for other works by this author on: GSW Google Scholar Environmental & Engineering Geoscience (2017) 23 (3): 179–190. https://doi.org/10.2113/gseegeosci.23.3.179 Article history first online: 15 Nov 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Sabrina Bonetto, Anna Facello, Gessica; Umili; A New Application of Curvatool Semi-automatic Approach To Qualitatively Detect Geological Lineaments. Environmental & Engineering Geoscience 2017;; 23 (3): 179–190. doi: https://doi.org/10.2113/gseegeosci.23.3.179 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyEnvironmental & Engineering Geoscience Search Advanced Search Abstract In the past years, lineament analysis has become an important analytical technique for delineation of major structural units in mineral prospecting, hydrogeology, and tectonic studies. The use of remote sensing, with progressive development of image enhancement techniques, provides an opportunity to produce more reliable and comprehensive lineament maps. In this paper, we propose the application of a semi-automatic approach based on digital terrain models (DTMs) for the extraction of potential lineaments and their detailed validation. We selected an area belonging to the Bagni di Vinadio municipality (Cuneo, NW Italy), which is part of the Argentera Massif (western Alps), as a test site. Data obtained from the code CurvaTool, developed by the authors, are successfully compared with literature information and with lineaments obtained from visual interpretation of remote sensing imagery. The CurvaTool code permits the extraction and classification of a greater number of linear features compared to visual interpretation techniques. The ability to detect features that are not perceptible by visual observation is a strong point of CurvaTool processing. In the test area, CurvaTool output data correlate with visually detected linear features and show a good correlation with regional tectonics and iso-kinematic maps from the literature. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.